Conceptual graph interchange format for mining financial statements

Siti Sakira Kamaruddin, Abdul Razak Hamdan, Azuraliza Abu Bakar, Fauzias Mat Nor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

This paper addresses the automatic transformation of financial statements into conceptual graph interchange format (CGIF). The method mainly involves extracting relevant financial performance indicators, parsing it to obtain syntactic sentence structure and to generate the CGIF for the extracted text. The required components for the transformation are detailed out with an illustrative example. The paper also discusses the potential manipulation of the resulting CGIF for knowledge discovery and more precisely for deviation detection.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages579-586
Number of pages8
Volume5589 LNAI
DOIs
Publication statusPublished - 2009
Event4th International Conference on Rough Sets and Knowledge Technology, RSKT 2009 - Gold Coast, QLD
Duration: 14 Jul 200916 Jul 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5589 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other4th International Conference on Rough Sets and Knowledge Technology, RSKT 2009
CityGold Coast, QLD
Period14/7/0916/7/09

Fingerprint

Conceptual Graphs
Interchanges
Mining
Performance Indicators
Parsing
Knowledge Discovery
Syntactics
Data mining
Manipulation
Deviation

Keywords

  • Conceptual Graph Interchange Format
  • Deviation Detection
  • Information Extraction
  • Text Mining

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Kamaruddin, S. S., Hamdan, A. R., Abu Bakar, A., & Mat Nor, F. (2009). Conceptual graph interchange format for mining financial statements. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5589 LNAI, pp. 579-586). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5589 LNAI). https://doi.org/10.1007/978-3-642-02962-2_73

Conceptual graph interchange format for mining financial statements. / Kamaruddin, Siti Sakira; Hamdan, Abdul Razak; Abu Bakar, Azuraliza; Mat Nor, Fauzias.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5589 LNAI 2009. p. 579-586 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5589 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kamaruddin, SS, Hamdan, AR, Abu Bakar, A & Mat Nor, F 2009, Conceptual graph interchange format for mining financial statements. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 5589 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5589 LNAI, pp. 579-586, 4th International Conference on Rough Sets and Knowledge Technology, RSKT 2009, Gold Coast, QLD, 14/7/09. https://doi.org/10.1007/978-3-642-02962-2_73
Kamaruddin SS, Hamdan AR, Abu Bakar A, Mat Nor F. Conceptual graph interchange format for mining financial statements. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5589 LNAI. 2009. p. 579-586. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-02962-2_73
Kamaruddin, Siti Sakira ; Hamdan, Abdul Razak ; Abu Bakar, Azuraliza ; Mat Nor, Fauzias. / Conceptual graph interchange format for mining financial statements. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5589 LNAI 2009. pp. 579-586 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{ec84cfcc30cf41c796d02c51e6a83bb4,
title = "Conceptual graph interchange format for mining financial statements",
abstract = "This paper addresses the automatic transformation of financial statements into conceptual graph interchange format (CGIF). The method mainly involves extracting relevant financial performance indicators, parsing it to obtain syntactic sentence structure and to generate the CGIF for the extracted text. The required components for the transformation are detailed out with an illustrative example. The paper also discusses the potential manipulation of the resulting CGIF for knowledge discovery and more precisely for deviation detection.",
keywords = "Conceptual Graph Interchange Format, Deviation Detection, Information Extraction, Text Mining",
author = "Kamaruddin, {Siti Sakira} and Hamdan, {Abdul Razak} and {Abu Bakar}, Azuraliza and {Mat Nor}, Fauzias",
year = "2009",
doi = "10.1007/978-3-642-02962-2_73",
language = "English",
isbn = "3642029612",
volume = "5589 LNAI",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "579--586",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - Conceptual graph interchange format for mining financial statements

AU - Kamaruddin, Siti Sakira

AU - Hamdan, Abdul Razak

AU - Abu Bakar, Azuraliza

AU - Mat Nor, Fauzias

PY - 2009

Y1 - 2009

N2 - This paper addresses the automatic transformation of financial statements into conceptual graph interchange format (CGIF). The method mainly involves extracting relevant financial performance indicators, parsing it to obtain syntactic sentence structure and to generate the CGIF for the extracted text. The required components for the transformation are detailed out with an illustrative example. The paper also discusses the potential manipulation of the resulting CGIF for knowledge discovery and more precisely for deviation detection.

AB - This paper addresses the automatic transformation of financial statements into conceptual graph interchange format (CGIF). The method mainly involves extracting relevant financial performance indicators, parsing it to obtain syntactic sentence structure and to generate the CGIF for the extracted text. The required components for the transformation are detailed out with an illustrative example. The paper also discusses the potential manipulation of the resulting CGIF for knowledge discovery and more precisely for deviation detection.

KW - Conceptual Graph Interchange Format

KW - Deviation Detection

KW - Information Extraction

KW - Text Mining

UR - http://www.scopus.com/inward/record.url?scp=69049101284&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=69049101284&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-02962-2_73

DO - 10.1007/978-3-642-02962-2_73

M3 - Conference contribution

SN - 3642029612

SN - 9783642029615

VL - 5589 LNAI

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 579

EP - 586

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -